Methods for finite population sampling.
Statistical models for environmental problems
Methods for finite population sampling.
1. Bayesian solutions for hierarchical superpopulation models
and small area inference.
2. Quasi-linear Bayesian approximations in finite populations,
in the presence of asymmetry and kurtosis: solution of non standard
models, with strong asymmetry and variable data quality.
3. Obtaining a part of Census information by means of a survey:
Assessment of alternative proposals for the sampling plan, related
both to the population definition and the strategy planning. The
strategy is composed by a sampling plan and an estimator.
Auxiliary information for municipalities is the instrument for
constructing the sampling plan.
Statistical models for environmental problems.
1. Development of hierarchical models and methods for air
quality indices.
2. Hierarchical models for Ensemble Weather Forecasting, which
are characterized by two main difficulties: first the number of
replicated scenarios is limited by the computing costs, second, the
forecasting error is not evaluated by means of observed data. The
forecasting error is modelled by means of observed data for
temperature.
3. Proposal of robust models for evaluating classification
errors in measurement systems capability models under a
two-component error model
